By Luke Miller | Thu, July 18, 24
We are excited to announce that after spending the winter and spring collecting data for an update to the Regional Energy Efficiency Database (REED), we are ready to present the updated REED Workbook with data for 2021, the Supporting Information report, and some findings from this newest round of data. This post describes what REED is, how it can be used, and dives into some interesting case studies.
What is REED?
REED is a database of energy efficiency program data for 12 jurisdictions: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Jersey, New Hampshire, New York, Pennsylvania, Rhode Island, Vermont, and Washington, D.C. In addition to the database, NEEP also publishes the Supporting Information Report, which provides helpful background information on each jurisdiction. NEEP has published REED data since 2013 (with data back to program year 2011). REED data includes annual and lifetime electric, gas, and other fuels energy savings (where applicable), demand savings, avoided air emissions, and program expenditures. Energy efficiency stakeholders across the region can use REED data to conduct analyses of efficiency programs and policy design, assist with air quality reporting, inform system planning, and compare energy efficiency impacts across states. The U.S. Energy Information Administration (EIA) uses REED data to inform its characterization of state energy efficiency programs in its National Energy Modeling System (NEMS), which models the US energy economy through 2050.
The newest version of the REED Workbook is available for public access via request.
Taking A Deeper Dive with REED Data
The data in the REED Workbook can provide valuable insights from across the landscape of energy efficiency programs in the Northeast. By analyzing savings, spending, program types, and emissions data in various ways, REED users can gain understanding around how different types of programs have functioned in different markets through the years. Below, we discuss a few of the ways this new data can help policymakers and program administrators understand the impacts of different energy efficiency programs in the NEEP region.
CO2 Reductions through Energy Efficiency
One important metric that REED data can show is the impact energy efficiency program investments have on lowering CO2 emissions. As shown in Figure 1, by dividing avoided CO2 emissions by total program spending, REED users can see emissions reductions per $1,000 spent per program. The graph below analyzes program data for 2020 and 2021. As the data shows, behavioral programs achieve higher average first-year annual CO2 reductions per dollar spent than other programs. Users could also analyze CO2 reductions over the lifetime of given program measures per investment. This analysis might provide better insights for programs with longer term savings, such as retrofits.
Increasing “Other Fuels” Savings
The data can also show the evolution of programs over time. In Vermont, where more recent energy efficiency programs have prioritized conversion of delivered fuel technologies to heat pumps, REED data shows how energy savings have changed across fuel types. Since 2018, the state has seen a slight decrease in annual electric and natural gas savings, but a large increase in other fuel savings per year. Figure 2 illustrates this change:
Achieving GHG Emissions Reductions
REED users can look at the impact that energy efficiency programs have on avoided GHG emissions over time. This is especially relevant as more states transition to using GHG emissions as metrics for energy efficiency programs. Maryland is one such state; starting in program year 2025, utilities must meet GHG emissions reduction goals. Interested parties can use REED to convert current savings data to emissions and see how the state is performing before these mandates are put in place. Figure 3 shows Maryland’s energy efficiency programs’ annual avoided CO2, NOx, and SO2 emissions since program year 2011.
Spending on Multifamily Programs
REED users can also examine spending over time by program category, such as multifamily building programs. Since REED started, multiple states in the NEEP region have instituted stronger equity goals that direct more funding to multifamily buildings and residents. Serving the multifamily sector is key to equitable program implementation because multifamily residents have, historically, largely fallen into the low- to moderate-income (LMI) category. Across the nation, 85 percent of multifamily households are considered LMI, and 39 percent of renters live in multifamily buildings. Low-income renters, particularly those living in small multifamily properties, tend to live in the least energy-efficient buildings. They also have higher relative energy burdens and are less likely to have the funds for energy retrofits. All these data points highlight the need for strong multifamily energy efficiency programs. Looking at New York, the REED data (in Figure 4) shows that spending on multifamily programs has trended upward throughout the lifetime of REED data collection.
New Metrics in REED
To improve the accuracy and quality of analysis that REED can facilitate, we have changed the data source we use to calculate avoided GHG emissions and transmission and distribution (T&D) losses. In previous iterations, we have used regional estimates of CO2, NOx, and SO2 emissions factors and T&D losses from ISO-NE, PJM, and NYISO to calculate each state’s reductions in air pollutants. Now, we have shifted to state-level estimates from the U.S. Energy Information Administration (EIA) for each REED state. Using these estimates allows us to more accurately report states’ avoided air emissions due to their reductions in electricity usage and the efficiency of each state’s transmission infrastructure. This change reflects the differences between generation technologies in each individual state.
Future Impacts and Use Cases
As states look towards the future of energy efficiency programs, exploring REED data from across the region can help inform program design. By looking at different types of programs and analyzing their energy savings and emissions reduction attributes, states will be able to fine-tune programs to meet their goals. REED users can look at trends on the program type and sector level, gaining insights into savings and spending trends over time and using this information to identify areas of focus. With access to this aggregated data in one convenient location, REED users will be well positioned to learn how to maximize the effectiveness of their energy efficiency programs for years to come.
U.S. Energy Information Administration funded the update to the REED database and Supporting Information Report. However, this article represents the opinions of the author. It is not meant to represent the position or opinions of the U.S. Energy Information Administration.